allensdk.brain_observatory.nwb package

Module contents

allensdk.brain_observatory.nwb.add_average_image(nwbfile, average_image, image_api=None)[source]
allensdk.brain_observatory.nwb.add_cell_specimen_table(nwbfile: pynwb.file.NWBFile, cell_specimen_table: pandas.core.frame.DataFrame, session_metadata: dict)[source]

This function takes the cell specimen table and writes the ROIs contained within. It writes these to a new NWB imaging plane based off the previously supplied metadata

Parameters:
nwbfile: NWBFile

this is the in memory NWBFile currently being written to which ROI data is added

cell_specimen_table: pd.DataFrame

this is the DataFrame containing the cells segmented from a ophys experiment, stored in json file and loaded. example: /home/nicholasc/projects/allensdk/allensdk/test/

brain_observatory/behavior/cell_specimen_table_789359614.json

session_metadata: dict

Dictionary containing cell_specimen_table related metadata. Should include at minimum the following fields:

“emission_lambda”, “excitation_lambda”, “indicator”, “targeted_structure”, and ophys_frame_rate”
Returns:
nwbfile: NWBFile

The altered in memory NWBFile object that now has a specimen table
allensdk.brain_observatory.nwb.add_corrected_fluorescence_traces(nwbfile, corrected_fluorescence_traces)[source]
allensdk.brain_observatory.nwb.add_dff_traces(nwbfile, dff_traces, ophys_timestamps)[source]
allensdk.brain_observatory.nwb.add_eye_gaze_data_interfaces(pynwb_container: pynwb.core.NWBContainer, pupil_areas: pandas.core.series.Series, eye_areas: pandas.core.series.Series, screen_coordinates: pandas.core.frame.DataFrame, screen_coordinates_spherical: pandas.core.frame.DataFrame, synced_timestamps: pandas.core.series.Series) → pynwb.core.NWBContainer[source]
allensdk.brain_observatory.nwb.add_eye_gaze_mapping_data_to_nwbfile(nwbfile: pynwb.file.NWBFile, eye_gaze_data: dict) → pynwb.file.NWBFile[source]
allensdk.brain_observatory.nwb.add_eye_tracking_ellipse_fit_data_to_nwbfile(nwbfile: pynwb.file.NWBFile, eye_dlc_tracking_data: dict, synced_timestamps: pandas.core.series.Series) → pynwb.file.NWBFile[source]
allensdk.brain_observatory.nwb.add_image(nwbfile, image_data, image_name, module_name, module_description, image_api=None)[source]
allensdk.brain_observatory.nwb.add_invalid_times(nwbfile, epochs)[source]

Write invalid times to nwbfile if epochs are not empty Parameters ———- nwbfile: pynwb.NWBFile epochs: list of dicts

records of invalid epochs
Returns:
pynwb.NWBFile
allensdk.brain_observatory.nwb.add_licks(nwbfile, licks)[source]
allensdk.brain_observatory.nwb.add_max_projection(nwbfile, max_projection, image_api=None)[source]
allensdk.brain_observatory.nwb.add_metadata(nwbfile, metadata: dict, behavior_only: bool)[source]
allensdk.brain_observatory.nwb.add_motion_correction(nwbfile, motion_correction)[source]
allensdk.brain_observatory.nwb.add_rewards(nwbfile, rewards_df)[source]
allensdk.brain_observatory.nwb.add_running_acquisition_to_nwbfile(nwbfile, running_acquisition_df: pandas.core.frame.DataFrame)[source]
allensdk.brain_observatory.nwb.add_running_speed_to_nwbfile(nwbfile, running_speed, name='speed', unit='cm/s', from_dataframe=False)[source]

Adds running speed data to an NWBFile as a timeseries in acquisition

Parameters:
nwbfile : pynwb.NWBFile

File to which running speeds will be written

running_speed : Union[RunningSpeed, pd.DataFrame]

Either a RunningSpeed object or pandas DataFrame. Contains attributes ‘values’ and ‘timestamps’

name : str, optional

Used as name of timeseries object

unit : str, optional

SI units of running speed values

from_dataframe : bool, optional

Whether running_speed is a dataframe or not. Default is False.
Returns:
nwbfile : pynwb.NWBFile
allensdk.brain_observatory.nwb.add_segmentation_mask_image(nwbfile, segmentation_mask_image, image_api=None)[source]
allensdk.brain_observatory.nwb.add_stimulus_index(nwbfile, stimulus_index, nwb_template)[source]
allensdk.brain_observatory.nwb.add_stimulus_presentations(nwbfile, stimulus_table, tag='stimulus_time_interval')[source]

Adds a stimulus table (defining stimulus characteristics for each time point in a session) to an nwbfile as TimeIntervals.

Parameters:
nwbfile : pynwb.NWBFile
stimulus_table: pd.DataFrame

Each row corresponds to an interval of time. Columns define the interval (start and stop time) and its characteristics. Nans in columns with string data will be replaced with the empty strings. Required columns are:

start_time :: the time at which this interval started stop_time :: the time at which this interval ended

tag : str, optional

Each interval in an nwb file has one or more tags. This string will be applied as a tag to all TimeIntervals created here
Returns:
nwbfile : pynwb.NWBFile
allensdk.brain_observatory.nwb.add_stimulus_template(nwbfile: pynwb.file.NWBFile, stimulus_template: allensdk.brain_observatory.behavior.stimulus_processing.stimulus_templates.StimulusTemplate)[source]
allensdk.brain_observatory.nwb.add_stimulus_timestamps(nwbfile, stimulus_timestamps, module_name='stimulus')[source]
allensdk.brain_observatory.nwb.add_task_parameters(nwbfile, task_parameters)[source]
allensdk.brain_observatory.nwb.add_trials(nwbfile, trials, description_dict={})[source]
allensdk.brain_observatory.nwb.check_nwbfile_version(nwbfile_path: str, desired_minimum_version: str, warning_msg: str)[source]
allensdk.brain_observatory.nwb.create_eye_gaze_mapping_dataframe(eye_gaze_data: dict) → pandas.core.frame.DataFrame[source]
allensdk.brain_observatory.nwb.create_eye_tracking_nwb_processing_module(eye_dlc_tracking_data: dict, synced_timestamps: pandas.core.series.Series) → pynwb.base.ProcessingModule[source]
allensdk.brain_observatory.nwb.create_gaze_mapping_nwb_processing_modules(eye_gaze_data: dict)[source]
allensdk.brain_observatory.nwb.create_stimulus_presentation_time_interval(name: str, description: str, columns_to_add: Iterable) → pynwb.epoch.TimeIntervals[source]
allensdk.brain_observatory.nwb.eye_tracking_data_is_valid(eye_dlc_tracking_data: dict, synced_timestamps: pandas.core.series.Series) → bool[source]
allensdk.brain_observatory.nwb.read_eye_dlc_tracking_ellipses(input_path: pathlib.Path) → dict[source]

Reads eye tracking ellipse fit data from an h5 file.

Args:
input_path (Path): Path to eye tracking ellipse fit h5 file
Returns:
dict: Loaded h5 data. Each ‘params’ field contains dataframes with]
ellipse fit parameters. Dataframes contain 5 columns each consisting of: “center_x”, “center_y”, “height”, “phi”, “width”
allensdk.brain_observatory.nwb.read_eye_gaze_mappings(input_path: pathlib.Path) → dict[source]

Reads eye gaze mapping data from an h5 file.

Args:
input_path (Path): Path to eye gaze mapping h5 data file produced by
‘allensdk.brain_observatory.gaze_mapping’ module.
Returns:
dict: Loaded h5 data.
*_eye_areas: Area of eye (in pixels^2) over time *_pupil_areas: Area of pupil (in pixels^2) over time *_screen_coordinates: y, x screen coordinates (in cm) over time *_screen_coordinates_spherical: y, x screen coordinates (in deg) over time synced_frame_timestamps: synced timestamps for video frames (in sec)
allensdk.brain_observatory.nwb.setup_table_for_epochs(table, timeseries, tag)[source]
allensdk.brain_observatory.nwb.setup_table_for_invalid_times(invalid_epochs)[source]

Create table with invalid times if invalid_epochs are present

Parameters:
invalid_epochs: list of dicts

of invalid epoch records
Returns:
pd.DataFrame of invalid times if epochs are not empty, otherwise return None